@article{doi:10.1021/acs.jctc.2c01085,
author = {Wang, Jinan and Do, Hung N. and Koirala, Kushal and Miao, Yinglong},
title = {Predicting Biomolecular Binding Kinetics: A Review},
journal = {Journal of Chemical Theory and Computation},
volume = {0},
number = {0},
pages = {null},
year = {0},
doi = {10.1021/acs.jctc.2c01085},
    note ={PMID: 36989090},

URL = { 
        https://doi.org/10.1021/acs.jctc.2c01085
    
},
eprint = { 
        https://doi.org/10.1021/acs.jctc.2c01085
    
}
}

@inproceedings{10.1145/3458817.3487397,
author = {Shaw, David E. and Adams, Peter J. and Azaria, Asaph and Bank, Joseph A. and Batson, Brannon and Bell, Alistair and Bergdorf, Michael and Bhatt, Jhanvi and Butts, J. Adam and Correia, Timothy and Dirks, Robert M. and Dror, Ron O. and Eastwood, Michael P. and Edwards, Bruce and Even, Amos and Feldmann, Peter and Fenn, Michael and Fenton, Christopher H. and Forte, Anthony and Gagliardo, Joseph and Gill, Gennette and Gorlatova, Maria and Greskamp, Brian and Grossman, J.P. and Gullingsrud, Justin and Harper, Anissa and Hasenplaugh, William and Heily, Mark and Heshmat, Benjamin Colin and Hunt, Jeremy and Ierardi, Douglas J. and Iserovich, Lev and Jackson, Bryan L. and Johnson, Nick P. and Kirk, Mollie M. and Klepeis, John L. and Kuskin, Jeffrey S. and Mackenzie, Kenneth M. and Mader, Roy J. and McGowen, Richard and McLaughlin, Adam and Moraes, Mark A. and Nasr, Mohamed H. and Nociolo, Lawrence J. and O'Donnell, Lief and Parker, Andrew and Peticolas, Jon L. and Pocina, Goran and Predescu, Cristian and Quan, Terry and Salmon, John K. and Schwink, Carl and Shim, Keun Sup and Siddique, Naseer and Spengler, Jochen and Szalay, Tamas and Tabladillo, Raymond and Tartler, Reinhard and Taube, Andrew G. and Theobald, Michael and Towles, Brian and Vick, William and Wang, Stanley C. and Wazlowski, Michael and Weingarten, Madeleine J. and Williams, John M. and Yuh, Kevin A.},
title = {Anton 3: Twenty Microseconds of Molecular Dynamics Simulation before Lunch},
year = {2021},
isbn = {9781450384421},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3458817.3487397},
doi = {10.1145/3458817.3487397},
abstract = {Anton 3 is the newest member in a family of supercomputers specially designed for atomic-level simulation of molecules relevant to biology (e.g., DNA, proteins, and drug molecules). Anton 3 achieves order-of-magnitude improvements in time-to-solution over its predecessor, Anton 2 (the current state of the art), and is over 100-fold faster than any other currently available supercomputer, thereby enabling broad new avenues of research on critical questions in biology and drug discovery. This speedup means that a 512-node Anton 3 simulates a million atoms at over 100 microseconds per day. Furthermore, Anton 3 attains this performance while consuming an order of magnitude less energy per simulated microsecond than any other machine. Like its predecessors, Anton 3 was designed from the ground up around a new custom chip to best exploit the capabilities offered by new technologies. We present here the main architectural and algorithmic developments that were necessary to achieve such significant advances.},
booktitle = {Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis},
articleno = {1},
numpages = {11},
location = {St. Louis, Missouri},
series = {SC '21}
}

@article{doi:10.1073/pnas.1303186110,
author = {Vittorio Limongelli  and Massimiliano Bonomi  and Michele Parrinello },
title = {Funnel metadynamics as accurate binding free-energy method},
journal = {Proceedings of the National Academy of Sciences},
volume = {110},
number = {16},
pages = {6358-6363},
year = {2013},
doi = {10.1073/pnas.1303186110},
URL = {https://www.pnas.org/doi/abs/10.1073/pnas.1303186110},
eprint = {https://www.pnas.org/doi/pdf/10.1073/pnas.1303186110},
abstract = {A detailed description of the events ruling ligand/protein interaction and an accurate estimation of the drug affinity to its target is of great help in speeding drug discovery strategies. We have developed a metadynamics-based approach, named funnel metadynamics, that allows the ligand to enhance the sampling of the target binding sites and its solvated states. This method leads to an efficient characterization of the binding free-energy surface and an accurate calculation of the absolute protein–ligand binding free energy. We illustrate our protocol in two systems, benzamidine/trypsin and SC-558/cyclooxygenase 2. In both cases, the X-ray conformation has been found as the lowest free-energy pose, and the computed protein–ligand binding free energy in good agreement with experiments. Furthermore, funnel metadynamics unveils important information about the binding process, such as the presence of alternative binding modes and the role of waters. The results achieved at an affordable computational cost make funnel metadynamics a valuable method for drug discovery and for dealing with a variety of problems in chemistry, physics, and material science.}}

@article{doi:10.1021/acs.jmedchem.6b00632,
author = {Mollica, Luca and Theret, Isabelle and Antoine, Mathias and Perron-Sierra, Françoise and Charton, Yves and Fourquez, Jean-Marie and Wierzbicki, Michel and Boutin, Jean A. and Ferry, Gilles and Decherchi, Sergio and Bottegoni, Giovanni and Ducrot, Pierre and Cavalli, Andrea},
title = {Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein–Ligand Residence Times},
journal = {Journal of Medicinal Chemistry},
volume = {59},
number = {15},
pages = {7167-7176},
year = {2016},
doi = {10.1021/acs.jmedchem.6b00632},
    note ={PMID: 27391254},

URL = { 
        https://doi.org/10.1021/acs.jmedchem.6b00632
    
},
eprint = { 
        https://doi.org/10.1021/acs.jmedchem.6b00632
    
}

}

@article{doi:10.1021/ja512751q,
author = {Wang, Lingle and Wu, Yujie and Deng, Yuqing and Kim, Byungchan and Pierce, Levi and Krilov, Goran and Lupyan, Dmitry and Robinson, Shaughnessy and Dahlgren, Markus K. and Greenwood, Jeremy and Romero, Donna L. and Masse, Craig and Knight, Jennifer L. and Steinbrecher, Thomas and Beuming, Thijs and Damm, Wolfgang and Harder, Ed and Sherman, Woody and Brewer, Mark and Wester, Ron and Murcko, Mark and Frye, Leah and Farid, Ramy and Lin, Teng and Mobley, David L. and Jorgensen, William L. and Berne, Bruce J. and Friesner, Richard A. and Abel, Robert},
title = {Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field},
journal = {Journal of the American Chemical Society},
volume = {137},
number = {7},
pages = {2695-2703},
year = {2015},
doi = {10.1021/ja512751q},
    note ={PMID: 25625324},

URL = { 
        https://doi.org/10.1021/ja512751q
    
},
eprint = { 
        https://doi.org/10.1021/ja512751q
    
}

}
@article{doi:10.1021/ct5000296,
author = {Homeyer, Nadine and Stoll, Friederike and Hillisch, Alexander and Gohlke, Holger},
title = {Binding Free Energy Calculations for Lead Optimization: Assessment of Their Accuracy in an Industrial Drug Design Context},
journal = {Journal of Chemical Theory and Computation},
volume = {10},
number = {8},
pages = {3331-3344},
year = {2014},
doi = {10.1021/ct5000296},
    note ={PMID: 26588302},

URL = { 
        https://doi.org/10.1021/ct5000296
    
},
eprint = { 
        https://doi.org/10.1021/ct5000296
    
}

}
@article{ZHANG2020107206,
title = {DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models},
journal = {Computer Physics Communications},
volume = {253},
pages = {107206},
year = {2020},
issn = {0010-4655},
doi = {https://doi.org/10.1016/j.cpc.2020.107206},
url = {https://www.sciencedirect.com/science/article/pii/S001046552030045X},
author = {Yuzhi Zhang and Haidi Wang and Weijie Chen and Jinzhe Zeng and Linfeng Zhang and Han Wang and Weinan E},
keywords = {Many-body potential energy, Deep learning, Concurrent learning},
abstract = {In recent years, promising deep learning based interatomic potential energy surface (PES) models have been proposed that can potentially allow us to perform molecular dynamics simulations for large scale systems with quantum accuracy. However, making these models truly reliable and practically useful is still a very non-trivial task. A key component in this task is the generation of datasets used in model training. In this paper, we introduce the Deep Potential GENerator (DP-GEN), an open-source software platform that implements the recently proposed ”on-the-fly” learning procedure (Zhang et al. 2019) and is capable of generating uniformly accurate deep learning based PES models in a way that minimizes human intervention and the computational cost for data generation and model training. DP-GEN automatically and iteratively performs three steps: exploration, labeling, and training. It supports various popular packages for these three steps: LAMMPS for exploration, Quantum Espresso, VASP, CP2K, etc. for labeling, and DeePMD-kit for training. It also allows automatic job submission and result collection on different types of machines, such as high performance clusters and cloud machines, and is adaptive to different job management tools, including Slurm, PBS, and LSF. As a concrete example, we illustrate the details of the process for generating a general-purpose PES model for Cu using DP-GEN.
Program summary
Program Title: DP-GEN Program Files doi: http://dx.doi.org/10.17632/sxybkgc5xc.1 Licensing provisions: LGPL Programming language: Python Nature of problem: Generating reliable deep learning based potential energy models with minimal human intervention and computational cost. Solution method: The concurrent learning scheme is implemented. Supports for sampling configuration space with LAMMPS, generating ab initio data with Quantum Espresso, VASP, CP2K and training potential models with DeePMD-kit are provided. Supports for different machines including workstations, high performance clusters and cloud machines are provided. Supports for job management tools including Slurm, PBS, LSF are provided.}
}
@article{SKEGGS1976737,
title = {The biochemistry of the renin-angiotensin system and its role in hypertension},
journal = {The American Journal of Medicine},
volume = {60},
number = {6},
pages = {737-748},
year = {1976},
note = {Symposium on Hypertension},
issn = {0002-9343},
doi = {https://doi.org/10.1016/0002-9343(76)90888-3},
url = {https://www.sciencedirect.com/science/article/pii/0002934376908883},
author = {Leonard T. Skeggs and Frederic E. Dorer and Joseph R. Kahn and Kenneth E. Lentz and Melvin Levine},
abstract = {The renin-angiotensin system has an important role in maintaining elevated blood pressure levels in certain forms of experimental and human hypertension. Renin, an enzyme produced by the juxtaglomerular cells of the kidney, acts on a protein substrate found in the alpha2-globulin fraction of the plasma to produce a decapeptide, angiotensin I. This decapeptide is not directly pressor, but on passage through the pulmonary circulation is converted to an octapeptide, angiotensin II, a very potent pressor substance which acts by causing constriction of arteriolar smooth muscle. In addition to its direct action which increases blood pressure, angiotensin II acts on the adrenal cortex to cause the release of the sodium-retaining hormone aldosterone. Recent evidence suggests that this action may be mediated by the heptapeptide, angiotensin III. Both renin and its protein substrate exist in multiple forms and renin may also exist as a high molecular-weight “pro-hormone,” although the physiologic significance of these forms is not clear. The elucidation of the biochemistry of the renin-angiotensin system has provided us with inhibitors which allow the system to be blocked effectively in vivo. Thus, angiotensin antagonists such as Sar1, Ile8-angiotensin II and converting enzyme inhibitors such as BPP9a (SQ 20881) have proved useful in the study of experimental and human hypertension.}
}

@article{10.1210/en.2003-0150,
    author = {Lavoie, Julie L. and Sigmund, Curt D.},
    title = "{Minireview: Overview of the Renin-Angiotensin System—An Endocrine and Paracrine System}",
    journal = {Endocrinology},
    volume = {144},
    number = {6},
    pages = {2179-2183},
    year = {2003},
    month = {06},
    abstract = "{Since the discovery of renin as a pressor substance in 1898, the renin-angiotensin (RAS) system has been extensively studied because it remains a prime candidate as a causative factor in the development and maintenance of hypertension. Indeed, some of the properties of the physiologically active component of the RAS, angiotensin II, include vasoconstriction, regulation of renal sodium and water absorption, and increasing thirst. Initially, its affect on blood pressure was thought to be mediated primarily through the classical endocrine pathway; that is, the generation of blood-borne angiotensin with actions in target tissues. More recently, however, it has become appreciated that a local autocrine or paracrine RAS may exist in a number of tissues, and that these may also play a significant role in regulating blood pressure. Some of the difficulties in studying tissue RAS stem from the limitations of pharmacology in not differentiating between RAS products made systemically from those synthesized locally. However, the development of transgenic animals with highly specific promoters to target the RAS to specific tissues provided important tools to dissect these systems. Thus, this minireview will discuss recent advances in understanding the relationship between endocrine and paracrine (tissue) RAS using transgenic models.}",
    issn = {0013-7227},
    doi = {10.1210/en.2003-0150},
    url = {https://doi.org/10.1210/en.2003-0150},
    eprint = {https://academic.oup.com/endo/article-pdf/144/6/2179/9294820/endo2179.pdf},
}
@article{doi:10.1056/NEJMoa030747,
author = {Drosten, Christian and G\"{u}nther, Stephan and Preiser, Wolfgang and van der Werf, Sylvie and Brodt, Hans-Reinhard and Becker, Stephan and Rabenau, Holger and Panning, Marcus and Kolesnikova, Larissa and Fouchier, Ron A.M. and Berger, Annemarie and Burgui\`{e}re, Ana-Maria and Cinatl, Jindrich and Eickmann, Markus and Escriou, Nicolas and Grywna, Klaus and Kramme, Stefanie and Manuguerra, Jean-Claude and M\"{u}ller, Stefanie and Rickerts, Volker and St\"{u}rmer, Martin and Vieth, Simon and Klenk, Hans-Dieter and Osterhaus, Albert D.M.E. and Schmitz, Herbert and Doerr, Hans Wilhelm},
title = {Identification of a Novel Coronavirus in Patients with Severe Acute Respiratory Syndrome},
journal = {New England Journal of Medicine},
volume = {348},
number = {20},
pages = {1967-1976},
year = {2003},
doi = {10.1056/NEJMoa030747},
    note ={PMID: 12690091},

URL = { 
        https://doi.org/10.1056/NEJMoa030747
    
},
eprint = { 
        https://doi.org/10.1056/NEJMoa030747
    
}

}

@Article{Fouchier2003,
author={Fouchier, Ron A. M.
and Kuiken, Thijs
and Schutten, Martin
and van Amerongen, Geert
and van Doornum, Gerard J. J.
and van den Hoogen, Bernadette G.
and Peiris, Malik
and Lim, Wilina
and St{\"o}hr, Klaus
and Osterhaus, Albert D. M. E.},
title={Koch's postulates fulfilled for SARS virus},
journal={Nature},
year={2003},
month={May},
day={01},
volume={423},
number={6937},
pages={240-240},
abstract={Severe acute respiratory syndrome (SARS) has recently emerged as a new human disease, resulting globally in 435 deaths from 6,234 probable cases (as of 3 May 2003). Here we provide proof from experimental infection of cynomolgus macaques (Macaca fascicularis) that the newly discovered SARS-associated coronavirus (SCV) is the aetiological agent of this disease. Our understanding of the aetiology of SARS will expedite the development of diagnostic tests, antiviral therapies and vaccines, and may allow a more concise case definition for this emerging disease.},
issn={1476-4687},
doi={10.1038/423240a},
url={https://doi.org/10.1038/423240a}
}


@Article{Li2003,
author={Li, Wenhui
and Moore, Michael J.
and Vasilieva, Natalya
and Sui, Jianhua
and Wong, Swee Kee
and Berne, Michael A.
and Somasundaran, Mohan
and Sullivan, John L.
and Luzuriaga, Katherine
and Greenough, Thomas C.
and Choe, Hyeryun
and Farzan, Michael},
title={Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus},
journal={Nature},
year={2003},
month={Nov},
day={01},
volume={426},
number={6965},
pages={450-454},
abstract={Spike (S) proteins of coronaviruses, including the coronavirus that causes severe acute respiratory syndrome (SARS), associate with cellular receptors to mediate infection of their target cells1,2. Here we identify a metallopeptidase, angiotensin-converting enzyme 2 (ACE2)3,4, isolated from SARS coronavirus (SARS-CoV)-permissive Vero E6 cells, that efficiently binds the S1 domain of the SARS-CoV S protein. We found that a soluble form of ACE2, but not of the related enzyme ACE1, blocked association of the S1 domain with Vero E6 cells. 293T cells transfected with ACE2, but not those transfected with human immunodeficiency virus-1 receptors, formed multinucleated syncytia with cells expressing S protein. Furthermore, SARS-CoV replicated efficiently on ACE2-transfected but not mock-transfected 293T cells. Finally, anti-ACE2 but not anti-ACE1 antibody blocked viral replication on Vero E6 cells. Together our data indicate that ACE2 is a functional receptor for SARS-CoV.},
issn={1476-4687},
doi={10.1038/nature02145},
url={https://doi.org/10.1038/nature02145}
}
@article{https://doi.org/10.1002/path.1570,
author = {Hamming, I and Timens, W and Bulthuis, MLC and Lely, AT and Navis, GJ and van Goor, H},
title = {Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis},
journal = {The Journal of Pathology},
volume = {203},
number = {2},
pages = {631-637},
keywords = {severe acute respiratory syndrome (SARS), coronavirus, angiotensin-converting enzyme 2, SARS-CoV receptor},
doi = {https://doi.org/10.1002/path.1570},
url = {https://pathsocjournals.onlinelibrary.wiley.com/doi/abs/10.1002/path.1570},
eprint = {https://pathsocjournals.onlinelibrary.wiley.com/doi/pdf/10.1002/path.1570},
abstract = {Abstract Severe acute respiratory syndrome (SARS) is an acute infectious disease that spreads mainly via the respiratory route. A distinct coronavirus (SARS-CoV) has been identified as the aetiological agent of SARS. Recently, a metallopeptidase named angiotensin-converting enzyme 2 (ACE2) has been identified as the functional receptor for SARS-CoV. Although ACE2 mRNA is known to be present in virtually all organs, its protein expression is largely unknown. Since identifying the possible route of infection has major implications for understanding the pathogenesis and future treatment strategies for SARS, the present study investigated the localization of ACE2 protein in various human organs (oral and nasal mucosa, nasopharynx, lung, stomach, small intestine, colon, skin, lymph nodes, thymus, bone marrow, spleen, liver, kidney, and brain). The most remarkable finding was the surface expression of ACE2 protein on lung alveolar epithelial cells and enterocytes of the small intestine. Furthermore, ACE2 was present in arterial and venous endothelial cells and arterial smooth muscle cells in all organs studied. In conclusion, ACE2 is abundantly present in humans in the epithelia of the lung and small intestine, which might provide possible routes of entry for the SARS-CoV. This epithelial expression, together with the presence of ACE2 in vascular endothelium, also provides a first step in understanding the pathogenesis of the main SARS disease manifestations. Copyright © 2004 Pathological Society of Great Britain and Ireland. Published by John Wiley \& Sons, Ltd.},
year = {2004}
}
@Article{Xu2020,
author={Xu, Hao
and Zhong, Liang
and Deng, Jiaxin
and Peng, Jiakuan
and Dan, Hongxia
and Zeng, Xin
and Li, Taiwen
and Chen, Qianming},
title={High expression of ACE2 receptor of 2019-nCoV on the epithelial cells of oral mucosa},
journal={International Journal of Oral Science},
year={2020},
month={Feb},
day={24},
volume={12},
number={1},
pages={8},
abstract={It has been reported that ACE2 is the main host cell receptor of 2019-nCoV and plays a crucial role in the entry of virus into the cell to cause the final infection. To investigate the potential route of 2019-nCov infection on the mucosa of oral cavity, bulk RNA-seq profiles from two public databases including The Cancer Genome Atlas (TCGA) and Functional Annotation of The Mammalian Genome Cap Analysis of Gene Expression (FANTOM5 CAGE) dataset were collected. RNA-seq profiling data of 13 organ types with para-carcinoma normal tissues from TCGA and 14 organ types with normal tissues from FANTOM5 CAGE were analyzed in order to explore and validate the expression of ACE2 on the mucosa of oral cavity. Further, single-cell transcriptomes from an independent data generated in-house were used to identify and confirm the ACE2-expressing cell composition and proportion in oral cavity. The results demonstrated that the ACE2 expressed on the mucosa of oral cavity. Interestingly, this receptor was highly enriched in epithelial cells of tongue. Preliminarily, those findings have explained the basic mechanism that the oral cavity is a potentially high risk for 2019-nCoV infectious susceptibility and provided a piece of evidence for the future prevention strategy in dental clinical practice as well as daily life.},
issn={2049-3169},
doi={10.1038/s41368-020-0074-x},
url={https://doi.org/10.1038/s41368-020-0074-x}
}

@article{https://doi.org/10.1002/jmv.25678,
author = {Lu, Hongzhou and Stratton, Charles W. and Tang, Yi-Wei},
title = {Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle},
journal = {Journal of Medical Virology},
volume = {92},
number = {4},
pages = {401-402},
doi = {https://doi.org/10.1002/jmv.25678},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jmv.25678},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmv.25678},
year = {2020}
}
@Article{Zhou2020,
author={Zhou, Peng
and Yang, Xing-Lou
and Wang, Xian-Guang
and Hu, Ben
and Zhang, Lei
and Zhang, Wei
and Si, Hao-Rui
and Zhu, Yan
and Li, Bei
and Huang, Chao-Lin
and Chen, Hui-Dong
and Chen, Jing
and Luo, Yun
and Guo, Hua
and Jiang, Ren-Di
and Liu, Mei-Qin
and Chen, Ying
and Shen, Xu-Rui
and Wang, Xi
and Zheng, Xiao-Shuang
and Zhao, Kai
and Chen, Quan-Jiao
and Deng, Fei
and Liu, Lin-Lin
and Yan, Bing
and Zhan, Fa-Xian
and Wang, Yan-Yi
and Xiao, Geng-Fu
and Shi, Zheng-Li},
title={A pneumonia outbreak associated with a new coronavirus of probable bat origin},
journal={Nature},
year={2020},
month={Mar},
day={01},
volume={579},
number={7798},
pages={270-273},
abstract={Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats1--4. Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans5--7. Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6{\%} sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96{\%} identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor---angiotensin converting enzyme II (ACE2)---as SARS-CoV.},
issn={1476-4687},
doi={10.1038/s41586-020-2012-7},
url={https://doi.org/10.1038/s41586-020-2012-7}
}

@article{10.1371/journal.ppat.1007236,
    doi = {10.1371/journal.ppat.1007236},
    author = {Song, Wenfei AND Gui, Miao AND Wang, Xinquan AND Xiang, Ye},
    journal = {PLOS Pathogens},
    publisher = {Public Library of Science},
    title = {Cryo-EM structure of the SARS coronavirus spike glycoprotein in complex with its host cell receptor ACE2},
    year = {2018},
    month = {08},
    volume = {14},
    url = {https://doi.org/10.1371/journal.ppat.1007236},
    pages = {1-19},
    abstract = {The trimeric SARS coronavirus (SARS-CoV) surface spike (S) glycoprotein consisting of three S1-S2 heterodimers binds the cellular receptor angiotensin-converting enzyme 2 (ACE2) and mediates fusion of the viral and cellular membranes through a pre- to postfusion conformation transition. Here, we report the structure of the SARS-CoV S glycoprotein in complex with its host cell receptor ACE2 revealed by cryo-electron microscopy (cryo-EM). The complex structure shows that only one receptor-binding domain of the trimeric S glycoprotein binds ACE2 and adopts a protruding “up” conformation. In addition, we studied the structures of the SARS-CoV S glycoprotein and its complexes with ACE2 in different in vitro conditions, which may mimic different conformational states of the S glycoprotein during virus entry. Disassociation of the S1-ACE2 complex from some of the prefusion spikes was observed and characterized. We also characterized the rosette-like structures of the clustered SARS-CoV S2 trimers in the postfusion state observed on electron micrographs. Structural comparisons suggested that the SARS-CoV S glycoprotein retains a prefusion architecture after trypsin cleavage into the S1 and S2 subunits and acidic pH treatment. However, binding to the receptor opens up the receptor-binding domain of S1, which could promote the release of the S1-ACE2 complex and S1 monomers from the prefusion spike and trigger the pre- to postfusion conformational transition.},
    number = {8},

}
@Article{South2020,
author={South, Andrew M.
and Tomlinson, Laurie
and Edmonston, Daniel
and Hiremath, Swapnil
and Sparks, Matthew A.},
title={Controversies of renin--angiotensin system inhibition during the COVID-19 pandemic},
journal={Nature Reviews Nephrology},
year={2020},
month={Jun},
day={01},
volume={16},
number={6},
pages={305-307},
abstract={The current COVID-19 pandemic is associated with unprecedented morbidity and mortality. Early reports suggested an association between disease severity and hypertension but did not account for sources of confounding. However, the responsible virus --- SARS-CoV-2 --- gains entry to host cells via angiotensin-converting enzyme 2 (ACE2), highlighting the need to understand the relationship between the virus and the renin--angiotensin system (RAS) and how this might be affected by RAS inhibitors.},
issn={1759-507X},
doi={10.1038/s41581-020-0279-4},
url={https://doi.org/10.1038/s41581-020-0279-4}
}

@Article{Kuba2005,
author={Kuba, Keiji
and Imai, Yumiko
and Rao, Shuan
and Gao, Hong
and Guo, Feng
and Guan, Bin
and Huan, Yi
and Yang, Peng
and Zhang, Yanli
and Deng, Wei
and Bao, Linlin
and Zhang, Binlin
and Liu, Guang
and Wang, Zhong
and Chappell, Mark
and Liu, Yanxin
and Zheng, Dexian
and Leibbrandt, Andreas
and Wada, Teiji
and Slutsky, Arthur S.
and Liu, Depei
and Qin, Chuan
and Jiang, Chengyu
and Penninger, Josef M.},
title={A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus--induced lung injury},
journal={Nature Medicine},
year={2005},
month={Aug},
day={01},
volume={11},
number={8},
pages={875-879},
abstract={During several months of 2003, a newly identified illness termed severe acute respiratory syndrome (SARS) spread rapidly through the world1,2,3. A new coronavirus (SARS-CoV) was identified as the SARS pathogen4,5,6,7, which triggered severe pneumonia and acute, often lethal, lung failure8. Moreover, among infected individuals influenza such as the Spanish flu9,10 and the emergence of new respiratory disease viruses11,12 have caused high lethality resulting from acute lung failure13. In cell lines, angiotensin-converting enzyme 2 (ACE2) has been identified as a potential SARS-CoV receptor14. The high lethality of SARS-CoV infections, its enormous economic and social impact, fears of renewed outbreaks as well as the potential misuse of such viruses as biologic weapons make it paramount to understand the pathogenesis of SARS-CoV. Here we provide the first genetic proof that ACE2 is a crucial SARS-CoV receptor in vivo. SARS-CoV infections and the Spike protein of the SARS-CoV reduce ACE2 expression. Notably, injection of SARS-CoV Spike into mice worsens acute lung failure in vivo that can be attenuated by blocking the renin-angiotensin pathway. These results provide a molecular explanation why SARS-CoV infections cause severe and often lethal lung failure and suggest a rational therapy for SARS and possibly other respiratory disease viruses.},
issn={1546-170X},
doi={10.1038/nm1267},
url={https://doi.org/10.1038/nm1267}
}

@article{YAZDANI2023121345,
title = {Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: Pharmacophore-based virtual screening, molecular docking, molecular dynamics and binding free energy studies},
journal = {Journal of Molecular Liquids},
volume = {375},
pages = {121345},
year = {2023},
issn = {0167-7322},
doi = {https://doi.org/10.1016/j.molliq.2023.121345},
url = {https://www.sciencedirect.com/science/article/pii/S0167732223001484},
author = {Mohsen Yazdani and Ameneh Jafari and Soodeh Mahdian and Mohsen Namazi and Sajjad Gharaghani},
keywords = {SARS-CoV-2, Drug design, Pharmacophore, Virtual screening, Molecular docking, Molecular dynamics, Protein–protein interaction},
abstract = {The lack of effective treatment remains a bottleneck in combating the current coronavirus family pandemic, particularly coronavirus 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The infection of host cells by SARS-CoV-2 is mediated by the binding of its receptor-binding domain (RBD) on the spike (S) glycoprotein to the host angiotensin-converting enzyme (ACE2) receptor. As all developed and available vaccines against COVID-19 do not provide long-term immunity, the creation of an effective drug for the treatment of COVID-19 is necessary and cannot be ignored. Therefore, the aim of this study is to present a computational screening method to identify potential inhibitor candidates with a high probability of blocking the binding of RBD to the ACE2 receptor. Pharmacophore mapping, molecular docking, molecular dynamics (MD) simulations, and binding free-energy analyses were performed to identify potential inhibitor candidates against ACE2/SARS-CoV-2. In conclusion, we propose the compound PubChem-84280085 as a potential inhibitor of protein–protein interactions to disrupt the binding of the SARS-CoV-2-RBD to the ACE2 receptor.}
}
@article{YI2022201,
title = {Natural triterpenoids from licorice potently inhibit SARS-CoV-2 infection},
journal = {Journal of Advanced Research},
volume = {36},
pages = {201-210},
year = {2022},
issn = {2090-1232},
doi = {https://doi.org/10.1016/j.jare.2021.11.012},
url = {https://www.sciencedirect.com/science/article/pii/S2090123221002307},
author = {Yang Yi and Junhua Li and Xinyuan Lai and Meng Zhang and Yi Kuang and Yang-Oujie Bao and Rong Yu and Wei Hong and Elishiba Muturi and Heng Xue and Hongping Wei and Tong Li and Hui Zhuang and Xue Qiao and Kuanhui Xiang and Hang Yang and Min Ye},
keywords = {COVID-19, SARS-CoV-2, Licorice, Licorice-saponin A3, Glycyrrhetinic acid},
abstract = {Introduction
The COVID-19 global epidemic caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a great public health emergency. Discovering antiviral drug candidates is urgent for the prevention and treatment of COVID-19.
Objectives
This work aims to discover natural SARS-CoV-2 inhibitors from the traditional Chinese herbal medicine licorice.
Methods
We screened 125 small molecules from Glycyrrhiza uralensis Fisch. (licorice, Gan-Cao) by virtual ligand screening targeting the receptor-binding domain (RBD) of SARS-CoV-2 spike protein. Potential hit compounds were further evaluated by ELISA, SPR, luciferase assay, antiviral assay and pharmacokinetic study.
Results
The triterpenoids licorice-saponin A3 (A3) and glycyrrhetinic acid (GA) could potently inhibit SARS-CoV-2 infection, with EC50 of 75 nM and 3.17 µM, respectively. Moreover, we reveal that A3 mainly targets the nsp7 protein, and GA binds to the spike protein RBD of SARS-CoV-2.
Conclusion
In this work, we found GA and A3 from licorice potently inhibit SARS-CoV-2 infection by affecting entry and replication of the virus. Our findings indicate that these triterpenoids may contribute to the clinical efficacy of licorice for COVID-19 and could be promising candidates for antiviral drug development.}
}





@article{https://doi.org/10.1002/aic.11932,
	author = {Maginn, Edward J.},
	title = {From discovery to data: What must happen for molecular simulation to become a mainstream chemical engineering tool},
	journal = {AIChE Journal},
	volume = {55},
	number = {6},
	pages = {1304-1310},
	keywords = {Monte Carlo, molecular dynamics, molecular simulation, molecular modeling, computational chemistry},
	doi = {https://doi.org/10.1002/aic.11932},
	url = {https://aiche.onlinelibrary.wiley.com/doi/abs/10.1002/aic.11932},
	eprint = {https://aiche.onlinelibrary.wiley.com/doi/pdf/10.1002/aic.11932},
	year = {2009}
}


@article{10.1093/bioinformatics/btt055,
	author = {Pronk, Sander and P\'all, Szil\'ard and Schulz, Roland and Larsson, Per and Bjelkmar, P\"ar and Apostolov, Rossen and Shirts, Michael R. and Smith, Jeremy C. and Kasson, Peter M. and van der Spoel, David and Hess, Berk and Lindahl, Erik},
	title = "{GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit}",
	journal = {Bioinformatics},
	volume = {29},
	number = {7},
	pages = {845-854},
	year = {2013},
	month = {02},
	abstract = "{Motivation: Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources.Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.Availability: GROMACS is an open source and free software available from http://www.gromacs.org.Contact:erik.lindahl@scilifelab.seSupplementary information:Supplementary data are available at Bioinformatics online.}",
	issn = {1367-4803},
	doi = {10.1093/bioinformatics/btt055},
	url = {https://doi.org/10.1093/bioinformatics/btt055},
	eprint = {https://academic.oup.com/bioinformatics/article-pdf/29/7/845/17343875/btt055.pdf},
}
@article{https://doi.org/10.1002/jcc.20289,
	author = {Phillips, James C. and Braun, Rosemary and Wang, Wei and Gumbart, James and Tajkhorshid, Emad and Villa, Elizabeth and Chipot, Christophe and Skeel, Robert D. and Kal\'e, Laxmikant and Schulten, Klaus},
	title = {Scalable molecular dynamics with NAMD},
	journal = {Journal of Computational Chemistry},
	volume = {26},
	number = {16},
	pages = {1781-1802},
	keywords = {biomolecular simulation, molecular dynamics, parallel computing},
	doi = {https://doi.org/10.1002/jcc.20289},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.20289},
	eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.20289},
	abstract = {Abstract NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu. © 2005 Wiley Periodicals, Inc. J Comput Chem 26: 1781-1802, 2005},
	year = {2005}
}
@article{doi:10.1063/5.0014475,
	author = {Phillips,James C.  and Hardy,David J.  and Maia,Julio D. C.  and Stone,John E.  and Ribeiro,Jo\~ao V.  and Bernardi,Rafael C.  and Buch,Ronak  and Fiorin,Giacomo  and H\'enin,J\'er\^ome  and Jiang,Wei  and McGreevy,Ryan  and Melo,Marcelo C. R.  and Radak,Brian K.  and Skeel,Robert D.  and Singharoy,Abhishek  and Wang,Yi  and Roux,Beno\^it  and Aksimentiev,Aleksei  and Luthey-Schulten,Zaida  and Kal\'e,Laxmikant V.  and Schulten,Klaus  and Chipot,Christophe  and Tajkhorshid,Emad },
	title = {Scalable molecular dynamics on CPU and GPU architectures with NAMD},
	journal = {The Journal of Chemical Physics},
	volume = {153},
	number = {4},
	pages = {044130},
	year = {2020},
	doi = {10.1063/5.0014475},
	
	URL = { 
	https://doi.org/10.1063/5.0014475
	
	},
	eprint = { 
	https://doi.org/10.1063/5.0014475
	
	}
	
}
@article{doi:10.1063/5.0013849,
	author = {Roe,Daniel R.  and Brooks,Bernard R. },
	title = {A protocol for preparing explicitly solvated systems for stable molecular dynamics simulations},
	journal = {The Journal of Chemical Physics},
	volume = {153},
	number = {5},
	pages = {054123},
	year = {2020},
	doi = {10.1063/5.0013849},
	
	URL = { 
	https://doi.org/10.1063/5.0013849
	
	},
	eprint = { 
	https://doi.org/10.1063/5.0013849
	
	}
	
}

//temp
@article {PMID:22582031,
	Title = {Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born},
	Author = {G\"otz, Andreas W and Williamson, Mark J and Xu, Dong and Poole, Duncan and Le Grand, Scott and Walker, Ross C},
	DOI = {10.1021/ct200909j},
	Number = {5},
	Volume = {8},
	Month = {May},
	Year = {2012},
	Journal = {Journal of chemical theory and computation},
	ISSN = {1549-9618},
	Pages = {1542-1555},
	Abstract = {We present an implementation of generalized Born implicit solvent all-atom classical molecular dynamics (MD) within the AMBER program package that runs entirely on CUDA enabled NVIDIA graphics processing units (GPUs). We discuss the algorithms that are used to exploit the processing power of the GPUs and show the performance that can be achieved in comparison to simulations on conventional CPU clusters. The implementation supports three different precision models in which the contributions to the forces are calculated in single precision floating point arithmetic but accumulated in double precision (SPDP), or everything is computed in single precision (SPSP) or double precision (DPDP). In addition to performance, we have focused on understanding the implications of the different precision models on the outcome of implicit solvent MD simulations. We show results for a range of tests including the accuracy of single point force evaluations and energy conservation as well as structural properties pertainining to protein dynamics. The numerical noise due to rounding errors within the SPSP precision model is sufficiently large to lead to an accumulation of errors which can result in unphysical trajectories for long time scale simulations. We recommend the use of the mixed-precision SPDP model since the numerical results obtained are comparable with those of the full double precision DPDP model and the reference double precision CPU implementation but at significantly reduced computational cost. Our implementation provides performance for GB simulations on a single desktop that is on par with, and in some cases exceeds, that of traditional supercomputers.},
	URL = {https://europepmc.org/articles/PMC3348677},
}
@article{doi:10.1021/ct400314y,
	author = {Salomon-Ferrer, Romelia and G\"otz, Andreas W. and Poole, Duncan and Le Grand, Scott and Walker, Ross C.},
	title = {Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 2. Explicit Solvent Particle Mesh Ewald},
	journal = {Journal of Chemical Theory and Computation},
	volume = {9},
	number = {9},
	pages = {3878-3888},
	year = {2013},
	doi = {10.1021/ct400314y},
	note ={PMID: 26592383},
	
	URL = { 
	https://doi.org/10.1021/ct400314y
	
	},
	eprint = { 
	https://doi.org/10.1021/ct400314y
	
	}
	
}
@article{doi:10.1063/1.448118,
	author = {Berendsen,H. J. C.  and Postma,J. P. M.  and van Gunsteren,W. F.  and DiNola,A.  and Haak,J. R. },
	title = {Molecular dynamics with coupling to an external bath},
	journal = {The Journal of Chemical Physics},
	volume = {81},
	number = {8},
	pages = {3684-3690},
	year = {1984},
	doi = {10.1063/1.448118},
	
	URL = { 
	https://doi.org/10.1063/1.448118
	
	},
	eprint = { 
	https://doi.org/10.1063/1.448118
	
	}
	
}


@article{doi:10.1063/1.1667473,
	author = {Uberuaga,Blas P.  and Anghel,Marian  and Voter,Arthur F. },
	title = {Synchronization of trajectories in canonical molecular-dynamics simulations: Observation, explanation, and exploitation},
	journal = {The Journal of Chemical Physics},
	volume = {120},
	number = {14},
	pages = {6363-6374},
	year = {2004},
	doi = {10.1063/1.1667473},
	
	URL = { 
	https://doi.org/10.1063/1.1667473
	
	},
	eprint = { 
	https://doi.org/10.1063/1.1667473
	
	}
	
}
@article{doi:10.1021/ct800573m,
	author = {Sindhikara, Daniel J. and Kim, Seonah and Voter, Arthur F. and Roitberg, Adrian E.},
	title = {Bad Seeds Sprout Perilous Dynamics: Stochastic Thermostat Induced Trajectory Synchronization in Biomolecules},
	journal = {Journal of Chemical Theory and Computation},
	volume = {5},
	number = {6},
	pages = {1624-1631},
	year = {2009},
	doi = {10.1021/ct800573m},
	note ={PMID: 26609854},
	
	URL = { 
	https://doi.org/10.1021/ct800573m
	
	},
	eprint = { 
	https://doi.org/10.1021/ct800573m
	
	}
	
}
@article{PhysRevA.33.4253,
	title = {Canonical dynamics of the Nos\'e oscillator: Stability, order, and chaos},
	author = {Posch, Harald A. and Hoover, William G. and Vesely, Franz J.},
	journal = {Phys. Rev. A},
	volume = {33},
	issue = {6},
	pages = {4253--4265},
	numpages = {0},
	year = {1986},
	month = {Jun},
	publisher = {American Physical Society},
	doi = {10.1103/PhysRevA.33.4253},
	url = {https://link.aps.org/doi/10.1103/PhysRevA.33.4253}
}
@article{doi:10.1063/1.4848716,
	author = {Omelyan,Igor  and Kovalenko,Andriy },
	title = {Multiple time step molecular dynamics in the optimized isokinetic ensemble steered with the molecular theory of solvation: Accelerating with advanced extrapolation of effective solvation forces},
	journal = {The Journal of Chemical Physics},
	volume = {139},
	number = {24},
	pages = {244106},
	year = {2013},
	doi = {10.1063/1.4848716},
	
	URL = { 
	https://doi.org/10.1063/1.4848716
	
	},
	eprint = { 
	https://doi.org/10.1063/1.4848716
	
	}
	
}
@article{doi:10.1063/1.4999447,
	author = {Chen,Pei-Yang  and Tuckerman,Mark E. },
	title = {Molecular dynamics based enhanced sampling of collective variables with very large time steps},
	journal = {The Journal of Chemical Physics},
	volume = {148},
	number = {2},
	pages = {024106},
	year = {2018},
	doi = {10.1063/1.4999447},
	
	URL = { 
	https://doi.org/10.1063/1.4999447
	
	},
	eprint = { 
	https://doi.org/10.1063/1.4999447
	
	}
}



@incollection{VITALIS200949,
	title = {Chapter 3 Methods for Monte Carlo Simulations of Biomacromolecules},
	booktitle = {Chapter 3 Methods for Monte Carlo Simulations of Biomacromolecules},
	editor = {Ralph A. Wheeler},
	series = {Annual Reports in Computational Chemistry},
	publisher = {Elsevier},
	volume = {5},
	pages = {49-76},
	year = {2009},
	issn = {1574-1400},
	doi = {https://doi.org/10.1016/S1574-1400(09)00503-9},
	url = {https://www.sciencedirect.com/science/article/pii/S1574140009005039},
	author = {Andreas Vitalis and Rohit V. Pappu},
	keywords = {Monte Carlo simulations, polypeptides, polynucleotides, concerted rotations, multicanonical ensemble, torsional space},
	abstract = {The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves and the applicability of such methods to simulations of biomacromolecules are discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, although underutilized in the biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse-graining strategies.}
}
@ARTICLE{10.3389/fmolb.2017.00087,
	
	AUTHOR={Wang, Changhao and Greene, D'Artagnan and Xiao, Li and Qi, Ruxi and Luo, Ray},   
	
	TITLE={Recent Developments and Applications of the MMPBSA Method},      
	
	JOURNAL={Frontiers in Molecular Biosciences},      
	
	VOLUME={4},           
	
	YEAR={2018},      
	
	URL={https://www.frontiersin.org/articles/10.3389/fmolb.2017.00087},       
	
	DOI={10.3389/fmolb.2017.00087},      
	
	ISSN={2296-889X},   
	
	ABSTRACT={The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.}
}
@article{doi:10.1021/acs.chemrev.9b00055,
	author = {Wang, Ercheng and Sun, Huiyong and Wang, Junmei and Wang, Zhe and Liu, Hui and Zhang, John Z. H. and Hou, Tingjun},
	title = {End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design},
	journal = {Chemical Reviews},
	volume = {119},
	number = {16},
	pages = {9478-9508},
	year = {2019},
	doi = {10.1021/acs.chemrev.9b00055},
	note ={PMID: 31244000},
	
	URL = { 
	https://doi.org/10.1021/acs.chemrev.9b00055
	
	},
	eprint = { 
	https://doi.org/10.1021/acs.chemrev.9b00055
	
	}
	
}
@Article{SousadaSilva2012,
	author={Sousa da Silva, Alan W.
	and Vranken, Wim F.},
	title={ACPYPE - AnteChamber PYthon Parser interfacE},
	journal={BMC Research Notes},
	year={2012},
	month={Jul},
	day={23},
	volume={5},
	number={1},
	pages={367},
	abstract={ACPYPE (or AnteChamber PYthon Parser interfacE) is a wrapper script around the ANTECHAMBER software that simplifies the generation of small molecule topologies and parameters for a variety of molecular dynamics programmes like GROMACS, CHARMM and CNS. It is written in the Python programming language and was developed as a tool for interfacing with other Python based applications such as the CCPN software suite (for NMR data analysis) and ARIA (for structure calculations from NMR data). ACPYPE is open source code, under GNU GPL v3, and is available as a stand-alone application at http://www.ccpn.ac.uk/acpypeand as a web portal application at http://webapps.ccpn.ac.uk/acpype.},
	issn={1756-0500},
	doi={10.1186/1756-0500-5-367},
	url={https://doi.org/10.1186/1756-0500-5-367}
}
@article{https://doi.org/10.1002/jcc.20035,
	author = {Wang, Junmei and Wolf, Romain M. and Caldwell, James W. and Kollman, Peter A. and Case, David A.},
	title = {Development and testing of a general amber force field},
	journal = {Journal of Computational Chemistry},
	volume = {25},
	number = {9},
	pages = {1157-1174},
	keywords = {general AMBER force field, additive force field, force field parameterization, restrained electrostatic potential (RESP)},
	doi = {https://doi.org/10.1002/jcc.20035},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.20035},
	eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.20035},
	abstract = {Abstract We describe here a general Amber force field (GAFF) for organic molecules. GAFF is designed to be compatible with existing Amber force fields for proteins and nucleic acids, and has parameters for most organic and pharmaceutical molecules that are composed of H, C, N, O, S, P, and halogens. It uses a simple functional form and a limited number of atom types, but incorporates both empirical and heuristic models to estimate force constants and partial atomic charges. The performance of GAFF in test cases is encouraging. In test I, 74 crystallographic structures were compared to GAFF minimized structures, with a root-mean-square displacement of 0.26 \r{A}, which is comparable to that of the Tripos 5.2 force field (0.25 \r{A}) and better than those of MMFF 94 and CHARMm (0.47 and 0.44 \r{A}, respectively). In test II, gas phase minimizations were performed on 22 nucleic acid base pairs, and the minimized structures and intermolecular energies were compared to MP2/6-31G* results. The RMS of displacements and relative energies were 0.25 \rA and 1.2 kcal/mol, respectively. These data are comparable to results from Parm99/RESP (0.16 \rA and 1.18 kcal/mol, respectively), which were parameterized to these base pairs. Test III looked at the relative energies of 71 conformational pairs that were used in development of the Parm99 force field. The RMS error in relative energies (compared to experiment) is about 0.5 kcal/mol. GAFF can be applied to wide range of molecules in an automatic fashion, making it suitable for rational drug design and database searching. @ 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1157-1174, 2004},
	year = {2004}
}
@article{WANG2006247,
	title = {Automatic atom type and bond type perception in molecular mechanical calculations},
	journal = {Journal of Molecular Graphics and Modelling},
	volume = {25},
	number = {2},
	pages = {247-260},
	year = {2006},
	issn = {1093-3263},
	doi = {https://doi.org/10.1016/j.jmgm.2005.12.005},
	url = {https://www.sciencedirect.com/science/article/pii/S1093326305001737},
	author = {Junmei Wang and Wei Wang and Peter A. Kollman and David A. Case},
	keywords = {Atom type perception, Bond type perception, Antechamber, Residue topology, Force field parameters, General AMBER force field (GAFF)},
	abstract = {In molecular mechanics (MM) studies, atom types and/or bond types of molecules are needed to determine prior to energy calculations. We present here an automatic algorithm of perceiving atom types that are defined in a description table, and an automatic algorithm of assigning bond types just based on atomic connectivity. The algorithms have been implemented in a new module of the AMBER packages. This auxiliary module, antechamber (roughly meaning "before AMBER"), can be applied to generate necessary inputs of leap-the AMBER program to generate topologies for minimization, molecular dynamics, etc., for most organic molecules. The algorithms behind the manipulations may be useful for other molecular mechanical packages as well as applications that need to designate atom types and bond types.}
}
@article{doi:10.1021/acs.jctc.5b00255,
	author = {Maier, James A. and Martinez, Carmenza and Kasavajhala, Koushik and Wickstrom, Lauren and Hauser, Kevin E. and Simmerling, Carlos},
	title = {ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB},
	journal = {Journal of Chemical Theory and Computation},
	volume = {11},
	number = {8},
	pages = {3696-3713},
	year = {2015},
	doi = {10.1021/acs.jctc.5b00255},
	note ={PMID: 26574453},
	
	URL = { 
	https://doi.org/10.1021/acs.jctc.5b00255
	
	},
	eprint = { 
	https://doi.org/10.1021/acs.jctc.5b00255
	
	}
	
}
@article{doi:10.1021/acs.jctc.1c00645,
	author = {Vald\'es-Tresanco, Mario S. and Vald\'es-Tresanco, Mario E. and Valiente, Pedro A. and Moreno, Ernesto},
	title = {gmx\_MMPBSA: A New Tool to Perform End-State Free Energy Calculations with GROMACS},
	journal = {Journal of Chemical Theory and Computation},
	volume = {17},
	number = {10},
	pages = {6281-6291},
	year = {2021},
	doi = {10.1021/acs.jctc.1c00645},
	note ={PMID: 34586825},
	
	URL = { 
	https://doi.org/10.1021/acs.jctc.1c00645
	
	},
	eprint = { 
	https://doi.org/10.1021/acs.jctc.1c00645
	
	}
	
}
@article{doi:10.1021/ct300418h,
	author = {Miller, Bill R. III and McGee, T. Dwight Jr. and Swails, Jason M. and Homeyer, Nadine and Gohlke, Holger and Roitberg, Adrian E.},
	title = {MMPBSA.py: An Efficient Program for End-State Free Energy Calculations},
	journal = {Journal of Chemical Theory and Computation},
	volume = {8},
	number = {9},
	pages = {3314-3321},
	year = {2012},
	doi = {10.1021/ct300418h},
	note ={PMID: 26605738},
	
	URL = { 
	https://doi.org/10.1021/ct300418h
	
	},
	eprint = { 
	https://doi.org/10.1021/ct300418h
	
	}
	
}
@article{doi:10.1021/ct300857j,
	author = {Eastman, Peter and Friedrichs, Mark S. and Chodera, John D. and Radmer, Randall J. and Bruns, Christopher M. and Ku, Joy P. and Beauchamp, Kyle A. and Lane, Thomas J. and Wang, Lee-Ping and Shukla, Diwakar and Tye, Tony and Houston, Mike and Stich, Timo and Klein, Christoph and Shirts, Michael R. and Pande, Vijay S.},
	title = {OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation},
	journal = {Journal of Chemical Theory and Computation},
	volume = {9},
	number = {1},
	pages = {461-469},
	year = {2013},
	doi = {10.1021/ct300857j},
	note ={PMID: 23316124},
	
	URL = { 
	https://doi.org/10.1021/ct300857j
	
	},
	eprint = { 
	https://doi.org/10.1021/ct300857j
	
	}
	
}
@article{doi:10.1021/acs.jctc.5b00935,
	author = {Lee, Jumin and Cheng, Xi and Swails, Jason M. and Yeom, Min Sun and Eastman, Peter K. and Lemkul, Justin A. and Wei, Shuai and Buckner, Joshua and Jeong, Jong Cheol and Qi, Yifei and Jo, Sunhwan and Pande, Vijay S. and Case, David A. and Brooks, Charles L. III and MacKerell, Alexander D. Jr. and Klauda, Jeffery B. and Im, Wonpil},
	title = {CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field},
	journal = {Journal of Chemical Theory and Computation},
	volume = {12},
	number = {1},
	pages = {405-413},
	year = {2016},
	doi = {10.1021/acs.jctc.5b00935},
	note ={PMID: 26631602},
	
	URL = { 
	https://doi.org/10.1021/acs.jctc.5b00935
	
	},
	eprint = { 
	https://doi.org/10.1021/acs.jctc.5b00935   
	}
}
@article{doi:10.1021/ar000033j,
	author = {Kollman, Peter A. and Massova, Irina and Reyes, Carolina and Kuhn, Bernd and Huo, Shuanghong and Chong, Lillian and Lee, Matthew and Lee, Taisung and Duan, Yong and Wang, Wei and Donini, Oreola and Cieplak, Piotr and Srinivasan, Jaysharee and Case, David A. and Cheatham, Thomas E.},
	title = {Calculating Structures and Free Energies of Complex Molecules: Combining Molecular Mechanics and Continuum Models},
	journal = {Accounts of Chemical Research},
	volume = {33},
	number = {12},
	pages = {889-897},
	year = {2000},
	doi = {10.1021/ar000033j},
	note ={PMID: 11123888},
	
	URL = { 
	https://doi.org/10.1021/ar000033j
	
	},
	eprint = { 
	https://doi.org/10.1021/ar000033j
	
	}
	
}
@article{Srinivasan1998ContinuumSS,
	title={Continuum Solvent Studies of the Stability of DNA, RNA, and Phosphoramidate-DNA Helices},
	author={Jayashree Srinivasan and Thomas E. Cheatham and Piotr Cieplak and Peter A. Kollman and David A. Case},
	journal={Journal of the American Chemical Society},
	year={1998},
	volume={120},
	pages={9401-9409}
}
@article{doi:10.1080/07391102.1998.10508279,
	author = { Jayashree   Srinivasan  and  Jennifer   Miller  and  Peter A. Kollman  and  David A.Case },
	title = {Continuum Solvent Studies of the Stability of RNA Hairpin Loops and Helices},
	journal = {Journal of Biomolecular Structure and Dynamics},
	volume = {16},
	number = {3},
	pages = {671-682},
	year  = {1998},
	publisher = {Taylor & Francis},
	doi = {10.1080/07391102.1998.10508279},
	note ={PMID: 10052623},
	
	URL = { 
	
	https://doi.org/10.1080/07391102.1998.10508279
	},
	eprint = { 
	https://doi.org/10.1080/07391102.1998.10508279  
	}
	
}

@article{https://doi.org/10.1002/wcms.1521,
	author = {Wang, Jinan and Arantes, Pablo R. and Bhattarai, Apurba and Hsu, Rohaine V. and Pawnikar, Shristi and Huang, Yu-ming M. and Palermo, Giulia and Miao, Yinglong},
	title = {Gaussian accelerated molecular dynamics: Principles and applications},
	journal = {WIREs Computational Molecular Science},
	volume = {11},
	number = {5},
	pages = {e1521},
	keywords = {drug binding, free energy calculations, enhanced sampling, membrane proteins, protein/nucleic acid complexes},
	doi = {https://doi.org/10.1002/wcms.1521},
	url = {https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/wcms.1521},
	eprint = {https://wires.onlinelibrary.wiley.com/doi/pdf/10.1002/wcms.1521},
	abstract = {Abstract Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., "Gaussian approximation"). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica-exchange GaMD (rex-GaMD) and replica-exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new "selective GaMD" algorithms including the Ligand GaMD (LiGaMD) and Peptide GaMD (Pep-GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small-molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein-protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods Molecular and Statistical Mechanics > Free Energy Methods},
	year = {2021}
}

@incollection{MIAO2017231,
	title = {Chapter Six - Gaussian Accelerated Molecular Dynamics: Theory, Implementation, and Applications},
	booktitle = {Chapter Six - Gaussian Accelerated Molecular Dynamics: Theory, Implementation, and Applications},
	editor = {David A. Dixon},
	series = {Annual Reports in Computational Chemistry},
	publisher = {Elsevier},
	volume = {13},
	pages = {231-278},
	year = {2017},
	issn = {1574-1400},
	doi = {https://doi.org/10.1016/bs.arcc.2017.06.005},
	url = {https://www.sciencedirect.com/science/article/pii/S1574140017300087},
	author = {Yinglong Miao and J. Andrew McCammon},
	keywords = {Gaussian Accelerated Molecular Dynamics, Biomolecules, Enhanced sampling, Free energy, Protein folding, Conformational transitions, Biomolecular recognition, Ligand binding},
	abstract = {A novel Gaussian Accelerated Molecular Dynamics (GaMD) method has been developed for simultaneous unconstrained enhanced sampling and free energy calculation of biomolecules. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of the biomolecules. Furthermore, by constructing a boost potential that follows a Gaussian distribution, accurate reweighting of GaMD simulations is achieved via cumulant expansion to the second order. The free energy profiles obtained from GaMD simulations allow us to identify distinct low energy states of the biomolecules and characterize biomolecular structural dynamics quantitatively. In this chapter, we present the theory of GaMD, its implementation in the widely used molecular dynamics software packages (AMBER and NAMD), and applications to the alanine dipeptide biomolecular model system, protein folding, biomolecular large-scale conformational transitions, and biomolecular recognition.}
}


@article{https://doi.org/10.1002/minf.201100135,
	author = {Homeyer, Nadine and Gohlke, Holger},
	title = {Free Energy Calculations by the Molecular Mechanics Poisson-Boltzmann Surface Area Method},
	journal = {Molecular Informatics},
	volume = {31},
	number = {2},
	pages = {114-122},
	keywords = {MM-PBSA, Binding affinity, Implicit solvent, Molecular recognition, Drug design},
	doi = {https://doi.org/10.1002/minf.201100135},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/minf.201100135},
	eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/minf.201100135},
	abstract = {Abstract Detailed knowledge of how molecules recognize interaction partners and of the conformational preferences of biomacromolecules is pivotal for understanding biochemical processes. Such knowledge also provides the foundation for the design of novel molecules, as undertaken in pharmaceutical research. Computer-based free energy calculations enable a detailed investigation of the energetic factors that are responsible for molecular stability or binding affinity. The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach is an efficient method for the calculation of free energies of diverse molecular systems. Here we describe the concepts of this approach and outline the practical proceeding. Furthermore we give an overview of the wide spectrum of problems that have been addressed with this method and of successful analyses carried out, thereby focussing on ambitious and recent studies. Limits of the approach in terms of accuracy and applicability are discussed. Despite these limitations MM-PBSA is a method with great potential that allows comparative free energy analyses for various molecular systems at low computational cost.},
	year = {2012}
}

@article{Sitkoff1994AccurateCO,
	title={Accurate Calculation of Hydration Free Energies Using Macroscopic Solvent Models},
	author={Doree Sitkoff and Kim A. Sharp and Barry Honig},
	journal={The Journal of Physical Chemistry},
	year={1994},
	volume={98},
	pages={1978-1988}
}
@article{https://doi.org/10.1107/S0021889883010985,
	author = {Connolly, M. L.},
	title = {Analytical molecular surface calculation},
	journal = {Journal of Applied Crystallography},
	volume = {16},
	number = {5},
	pages = {548-558},
	doi = {https://doi.org/10.1107/S0021889883010985},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1107/S0021889883010985},
	eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1107/S0021889883010985},
	abstract = {A computer algorithm is presented for calculating the part of the van der Waals surface of molecule that is accessible to solvent. The solvent molecule is modeled by a sphere. This sphere is, in effect, rolled over the molecule to generate a smooth outer-surface contour. This surface contour is made up of pieces of spheres and tori that join at circular arcs. The spheres, tori and arcs are defined by analytical expressions in terms of the atomic coordinates, van der Waals radii and the probe radius. The area of each surface piece may be calculated analytically and the surface may be displayed on either vector or raster computer-graphics systems. These methods are useful for studying the structure and interactions of proteins and nucleic acids.},
	year = {1983}
}

@article{https://doi.org/10.1002/jcc.21372,
	author = {Rastelli, Giulio and Rio, Alberto Del and Degliesposti, Gianluca and Sgobba, Miriam},
	title = {Fast and accurate predictions of binding free energies using MM-PBSA and MM-GBSA},
	journal = {Journal of Computational Chemistry},
	volume = {31},
	number = {4},
	pages = {797-810},
	keywords = {binding free energy prediction, MM-PBSA, MM-GBSA, virtual screening, drug design},
	doi = {https://doi.org/10.1002/jcc.21372},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.21372},
	eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.21372},
	abstract = {Abstract In the drug discovery process, accurate methods of computing the affinity of small molecules with a biological target are strongly needed. This is particularly true for molecular docking and virtual screening methods, which use approximated scoring functions and struggle in estimating binding energies in correlation with experimental values. Among the various methods, MM-PBSA and MM-GBSA are emerging as useful and effective approaches. Although these methods are typically applied to large collections of equilibrated structures of protein-ligand complexes sampled during molecular dynamics in water, the possibility to reliably estimate ligand affinity using a single energy-minimized structure and implicit solvation models has not been explored in sufficient detail. Herein, we thoroughly investigate this hypothesis by comparing different methods for the generation of protein-ligand complexes and diverse methods for free energy prediction for their ability to correlate with experimental values. The methods were tested on a series of structurally diverse inhibitors of Plasmodium falciparum DHFR with known binding mode and measured affinities. The results showed that correlations between MM-PBSA or MM-GBSA binding free energies with experimental affinities were in most cases excellent. Importantly, we found that correlations obtained with the use of a single protein-ligand minimized structure and with implicit solvation models were similar to those obtained after averaging over multiple MD snapshots with explicit water molecules, with consequent save of computing time without loss of accuracy. When applied to a virtual screening experiment, such an approach proved to discriminate between true binders and decoy molecules and yielded significantly better enrichment curves. @ 2009 Wiley Periodicals, Inc. J Comput Chem, 2010},
	year = {2010}
}

@article{LEE2006864,
	title = {Calculation of Absolute Protein-Ligand Binding Affinity Using Path and Endpoint Approaches},
	journal = {Biophysical Journal},
	volume = {90},
	number = {3},
	pages = {864-877},
	year = {2006},
	issn = {0006-3495},
	doi = {https://doi.org/10.1529/biophysj.105.071589},
	url = {https://www.sciencedirect.com/science/article/pii/S0006349506722743},
	author = {Michael S. Lee and Mark A. Olson},
	abstract = {A comparative analysis is provided of rigorous and approximate methods for calculating absolute binding affinities of two protein-ligand complexes: the FKBP protein bound with small molecules 4-hydroxy-2-butanone and FK506. Our rigorous approach is an umbrella sampling technique where a potential of mean force is determined by pulling the ligand out of the protein active site over several simulation windows. The results of this approach agree well with experimentally observed binding affinities. Also assessed is a commonly used approximate endpoint approach, which separately estimates enthalpy, solvation free energy, and entropy. We show that this endpoint approach has numerous variations, all of which are prone to critical shortcomings. For example, conventional harmonic and quasiharmonic entropy estimation procedures produce disparate results for the relatively simple protein-ligand systems studied in this work.}
}
@article{doi:10.1063/1.3073889,
	author = {Bussi,Giovanni  and Zykova-Timan,Tatyana  and Parrinello,Michele },
	title = {Isothermal-isobaric molecular dynamics using stochastic velocity rescaling},
	journal = {The Journal of Chemical Physics},
	volume = {130},
	number = {7},
	pages = {074101},
	year = {2009},
	doi = {10.1063/1.3073889},
	
	URL = { 
	https://doi.org/10.1063/1.3073889
	
	},
	eprint = { 
	https://doi.org/10.1063/1.3073889
	
	}
	
}
@manual{amber,
	author = "D.A. Case and H.M. Aktulga and K. Belfon and I.Y. Ben-Shalom and J.T. Berryman and S.R. Brozell and D.S. Cerutti and T.E. Cheatham and III and G.A. Cisneros and V.W.D. Cruzeiro and T.A. Darden and R.E. Duke and G. Giambasu and M.K. Gilson and H. Gohlke and A.W. Goetz and R. Harris and S. Izadi and S.A. Izmailov and K. Kasavajhala and M.C. Kaymak and E. King and A. Kovalenko and T. Kurtzman and T.S. Lee and S. LeGrand and P. Li and C. Lin and J. Liu and T. Luchko and R. Luo and M. Machado and V. Man and M. Manathunga and K.M. Merz and Y. Miao and O. Mikhailovskii and G. Monard and H. Nguyen and K.A. O'Hearn and A. Onufriev and F. Pan and S. Pantano and R. Qi, A. Rahnamoun and D.R. Roe and A. Roitberg and C. Sagui and S. Schott-Verdugo and A. Shajan and J. Shen and C.L. Simmerling and N.R. Skrynnikov and J. Smith and J. Swails and R.C. Walker and J. Wang and J. Wang and H. Wei and R.M. Wolf and X. Wu and Y. Xiong and Y. Xue and D.M. York and S. Zhao and P.A. Kollman (2022)",
	booktitle = {Amber 2022},
	title = {Amber 2022},
	organization= {University of California, San Francisco},
	year = {2022},
	
	
}
@article{doi:10.1021/ct8000365,
	author = {Lingenheil, M. and Denschlag, R. and Reichold, R. and Tavan, P.},
	title = {The "Hot-Solvent/Cold-Solute" Problem Revisited},
	journal = {Journal of Chemical Theory and Computation},
	volume = {4},
	number = {8},
	pages = {1293-1306},
	year = {2008},
	doi = {10.1021/ct8000365},
	note ={PMID: 26631705},
	
	URL = { 
	https://doi.org/10.1021/ct8000365
	
	},
	eprint = { 
	https://doi.org/10.1021/ct8000365
	
	}
	
}
@article{doi:10.1021/ct400109a,
	author = {Basconi, Joseph E. and Shirts, Michael R.},
	title = {Effects of Temperature Control Algorithms on Transport Properties and Kinetics in Molecular Dynamics Simulations},
	journal = {Journal of Chemical Theory and Computation},
	volume = {9},
	number = {7},
	pages = {2887-2899},
	year = {2013},
	doi = {10.1021/ct400109a},
	note ={PMID: 26583973},
	
	URL = { 
	https://doi.org/10.1021/ct400109a
	
	},
	eprint = { 
	https://doi.org/10.1021/ct400109a
	
	}
	
}
@misc{amber_tutorial,
	
	author = {Dwight McGee, Bill Miller III, & Jason Swails},
	
	title = {Python Script MMPBSA.py},
	
	howpublished={\url{https://ambermd.org/tutorials/advanced/tutorial3/py_script/index.php/}},
	
	year = {2009}
	
}
@article{10.1063/1.2943146,
	author = {Kleinerman,Dana S.  and Czaplewski,Cezary  and Liwo,Adam  and Scheraga,Harold A. },
	title = {Implementations of Nosé–Hoover and Nosé–Poincaré thermostats in mesoscopic dynamic simulations with the united-residue model of a polypeptide chain},
	journal = {The Journal of Chemical Physics},
	volume = {128},
	number = {24},
	pages = {245103},
	year = {2008},
	doi = {10.1063/1.2943146},
	
	URL = { 
	https://doi.org/10.1063/1.2943146
	
	},
	eprint = { 
	https://doi.org/10.1063/1.2943146
	
	}
	
}


@article{doi:10.1063/5.0019056,
	author = {He,Xibing  and Man,Viet H.  and Yang,Wei  and Lee,Tai-Sung  and Wang,Junmei },
	title = {A fast and high-quality charge model for the next generation general AMBER force field},
	journal = {The Journal of Chemical Physics},
	volume = {153},
	number = {11},
	pages = {114502},
	year = {2020},
	doi = {10.1063/5.0019056},
	
	URL = { 
	https://doi.org/10.1063/5.0019056
	
	},
	eprint = { 
	https://doi.org/10.1063/5.0019056
	
	}
	
}

@article{model1,
	author = {Jakalian, Araz and Bush, Bruce L. and Jack, David B. and Bayly, Christopher I.},
	title = {Fast, efficient generation of high-quality atomic charges. AM1-BCC model: I. Method},
	journal = {Journal of Computational Chemistry},
	volume = {21},
	number = {2},
	pages = {132-146},
	doi = {https://doi.org/10.1002/(SICI)1096-987X(20000130)21:2<132::AID-JCC5>3.0.CO;2-P},
	year = {2000}
}

@article{model2,
	author = {Jakalian, Araz and Jack, David B. and Bayly, Christopher I.},
	title = {Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation},
	journal = {Journal of Computational Chemistry},
	volume = {23},
	number = {16},
	pages = {1623-1641},
	doi = {https://doi.org/10.1002/jcc.10128},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.10128},
	eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.10128},
	year = {2002}
}
@article{article,
	author = {Zhiyong, Cui and Zhang, Zhiwei and Zhou, Tianxing and Zhou, Xueke and Zhang, Yin and Meng, Hengli and Wang, Wenli and Liu, Yuan},
	year = {2022},
	month = {11},
	pages = {134812},
	title = {A TastePeptides-Meta system including an umami/bitter classification model Umami\_YYDS, a TastePeptidesDB database and an open-source package Auto\_Taste\_ML},
	volume = {405},
	journal = {Food Chemistry},
	doi = {10.1016/j.foodchem.2022.134812}
}

@article{DONG2020533,
title = {An interactive web-based dashboard to track COVID-19 in real time},
journal = {The Lancet Infectious Diseases},
volume = {20},
number = {5},
pages = {533-534},
year = {2020},
issn = {1473-3099},
doi = {https://doi.org/10.1016/S1473-3099(20)30120-1},
url = {https://www.sciencedirect.com/science/article/pii/S1473309920301201},
author = {Ensheng Dong and Hongru Du and Lauren Gardner}
}


@article{doi:10.1073/pnas.2003138117,
author = {Jian Shang  and Yushun Wan  and Chuming Luo  and Gang Ye  and Qibin Geng  and Ashley Auerbach  and Fang Li },
title = {Cell entry mechanisms of SARS-CoV-2},
journal = {Proceedings of the National Academy of Sciences},
volume = {117},
number = {21},
pages = {11727-11734},
year = {2020},
doi = {10.1073/pnas.2003138117},
URL = {https://www.pnas.org/doi/abs/10.1073/pnas.2003138117},
eprint = {https://www.pnas.org/doi/pdf/10.1073/pnas.2003138117},
abstract = {A novel severe acute respiratory syndrome (SARS)-like coronavirus (SARS-CoV-2) is causing the global coronavirus disease 2019 (COVID-19) pandemic. Understanding how SARS-CoV-2 enters human cells is a high priority for deciphering its mystery and curbing its spread. A virus surface spike protein mediates SARS-CoV-2 entry into cells. To fulfill its function, SARS-CoV-2 spike binds to its receptor human ACE2 (hACE2) through its receptor-binding domain (RBD) and is proteolytically activated by human proteases. Here we investigated receptor binding and protease activation of SARS-CoV-2 spike using biochemical and pseudovirus entry assays. Our findings have identified key cell entry mechanisms of SARS-CoV-2. First, SARS-CoV-2 RBD has higher hACE2 binding affinity than SARS-CoV RBD, supporting efficient cell entry. Second, paradoxically, the hACE2 binding affinity of the entire SARS-CoV-2 spike is comparable to or lower than that of SARS-CoV spike, suggesting that SARS-CoV-2 RBD, albeit more potent, is less exposed than SARS-CoV RBD. Third, unlike SARS-CoV, cell entry of SARS-CoV-2 is preactivated by proprotein convertase furin, reducing its dependence on target cell proteases for entry. The high hACE2 binding affinity of the RBD, furin preactivation of the spike, and hidden RBD in the spike potentially allow SARS-CoV-2 to maintain efficient cell entry while evading immune surveillance. These features may contribute to the wide spread of the virus. Successful intervention strategies must target both the potency of SARS-CoV-2 and its evasiveness.}}


@article{DEATON2008732,
title = {Thiol-based angiotensin-converting enzyme 2 inhibitors: P1 modifications for the exploration of the S1 subsite},
journal = {Bioorganic \& Medicinal Chemistry Letters},
volume = {18},
number = {2},
pages = {732-737},
year = {2008},
issn = {0960-894X},
doi = {https://doi.org/10.1016/j.bmcl.2007.11.048},
url = {https://www.sciencedirect.com/science/article/pii/S0960894X07013583},
author = {David N. Deaton and Enoch N. Gao and Kevin P. Graham and Jeffrey W. Gross and Aaron B. Miller and John M. Strelow},
keywords = {Angiotensin-converting enzyme 2, Metalloproteases, Protease inhibitors, Thiols},
abstract = {Screening of a metalloprotease library led to the identification of a thiol-based dual ACE/NEP inhibitor as a potent ACE2 inhibitor. Modifications of the P1 benzyl moiety led to improvements in ACE2 potency as well as to increased selectivity versus ACE and NEP.}
}

@article{MA2021113857,
title = {Screening S protein - ACE2 blockers from natural products: Strategies and advances in the discovery of potential inhibitors of COVID-19},
journal = {European Journal of Medicinal Chemistry},
volume = {226},
pages = {113857},
year = {2021},
issn = {0223-5234},
doi = {https://doi.org/10.1016/j.ejmech.2021.113857},
url = {https://www.sciencedirect.com/science/article/pii/S0223523421007066},
author = {Le-le Ma and Hui-min Liu and Xue-mei Liu and Xiao-yu Yuan and Chao Xu and Fang Wang and Jun-zhi Lin and Run-chun Xu and Ding-kun Zhang},
keywords = {COVID-19, ACE2, S protein, Drug screening technology, Natural products},
abstract = {The Coronavirus disease, 2019 (COVID-19) is caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), which poses a major threat to human life and health. Given its continued development, limiting the spread of COVID-19 in the population remains a challenging task. Currently, multiple therapies are being tried around the world to deal with SARS-CoV-2 infection, and a variety of studies have shown that natural products have a significant effect on COVID-19 patients. The combination of SARS-CoV-2 S protein with Angiotensin converting enzyme II(ACE2) of host cell to promote membrane fusion is an initial critical step for SARS-CoV-2 infection. Therefore, screening natural products that inhibit the binding of SARS-CoV-2 S protein and ACE2 also provides a feasible strategy for the treatment of COVID-19. Establishment of high throughput screening model is an important basis and key technology for screening S protein-ACE2 blockers. Based on this, the molecular structures of SARS-CoV-2 and ACE2 and their processes in the life cycle of SARS-CoV-2 and host cell infection were firstly reviewed in this paper, with emphasis on the methods and techniques of screening S protein-ACE2 blockers, including Virtual Screening (VS), Surface Plasmon Resonance (SPR), Biochromatography, Biotin-avidin with Enzyme-linked Immunosorbent assay and Gene Chip Technology. Furthermore, the technical principle, advantages and disadvantages and application scope were further elaborated. Combined with the application of the above screening technologies in S protein-ACE2 blockers, a variety of natural products, such as flavonoids, terpenoids, phenols, alkaloids, were summarized, which could be used as S protein-ACE2 blockers, in order to provide ideas for the efficient discovery of S protein-ACE2 blockers from natural sources and contribute to the development of broad-spectrum anti coronavirus drugs.}
}
@Article{Wu2022,
author={Wu, Leyun
and Zhou, Liping
and Mo, Mengxia
and Liu, Tingting
and Wu, Chengkun
and Gong, Chunye
and Lu, Kai
and Gong, Likun
and Zhu, Weiliang
and Xu, Zhijian},
title={SARS-CoV-2 Omicron RBD shows weaker binding affinity than the currently dominant Delta variant to human ACE2},
journal={Signal Transduction and Targeted Therapy},
year={2022},
month={Jan},
day={05},
volume={7},
number={1},
pages={8},
issn={2059-3635},
doi={10.1038/s41392-021-00863-2},
url={https://doi.org/10.1038/s41392-021-00863-2}
}

@Article{Sepehrinezhad2020,
author={Sepehrinezhad, Ali
and Shahbazi, Ali
and Negah, Sajad Sahab},
title={COVID-19 virus may have neuroinvasive potential and cause neurological complications: a perspective review},
journal={Journal of NeuroVirology},
year={2020},
month={Jun},
day={01},
volume={26},
number={3},
pages={324-329},
abstract={Coronavirus disease 2019 (COVID-19) was reported at the end of 2019 in China for the first time and has rapidly spread throughout the world as a pandemic. Since COVID-19 causes mild to severe acute respiratory syndrome, most studies in this field have only focused on different aspects of pathogenesis in the respiratory system. However, evidence suggests that COVID-19 may affect the central nervous system (CNS). Given the outbreak of COVID-19, it seems necessary to perform investigations on the possible neurological complications in patients who suffered from COVID-19. Here, we reviewed the evidence of the neuroinvasive potential of coronaviruses and discussed the possible pathogenic processes in CNS infection by COVID-19 to provide a precise insight for future studies.},
issn={1538-2443},
doi={10.1007/s13365-020-00851-2},
url={https://doi.org/10.1007/s13365-020-00851-2}
}
@Article{Bhalla2021,
author={Bhalla, Vivek
and Blish, Catherine A.
and South, Andrew M.},
title={A historical perspective on ACE2 in the COVID-19 era},
journal={Journal of Human Hypertension},
year={2021},
month={Oct},
day={01},
volume={35},
number={10},
pages={935-939},
issn={1476-5527},
doi={10.1038/s41371-020-00459-3},
url={https://doi.org/10.1038/s41371-020-00459-3}
}
@article{10.1093/nar/gkr777,
    author = {Gaulton, Anna and Bellis, Louisa J. and Bento, A. Patricia and Chambers, Jon and Davies, Mark and Hersey, Anne and Light, Yvonne and McGlinchey, Shaun and Michalovich, David and Al-Lazikani, Bissan and Overington, John P.},
    title = "{ChEMBL: a large-scale bioactivity database for drug discovery}",
    journal = {Nucleic Acids Research},
    volume = {40},
    number = {D1},
    pages = {D1100-D1107},
    year = {2011},
    month = {09},
    abstract = "{ChEMBL is an Open Data database containing binding, functional and ADMET information for a large number of drug-like bioactive compounds. These data are manually abstracted from the primary published literature on a regular basis, then further curated and standardized to maximize their quality and utility across a wide range of chemical biology and drug-discovery research problems. Currently, the database contains 5.4 million bioactivity measurements for more than 1 million compounds and 5200 protein targets. Access is available through a web-based interface, data downloads and web services at: https://www.ebi.ac.uk/chembldb.}",
    issn = {0305-1048},
    doi = {10.1093/nar/gkr777},
    url = {https://doi.org/10.1093/nar/gkr777},
    eprint = {https://academic.oup.com/nar/article-pdf/40/D1/D1100/16955876/gkr777.pdf},
}

@ARTICLE{10.3389/fphar.2020.00439,
  
AUTHOR={Liu, Zhihong and Cai, Chuipu and Du, Jiewen and Liu, Bingdong and Cui, Lu and Fan, Xiude and Wu, Qihui and Fang, Jiansong and Xie, Liwei},   
	 
TITLE={TCMIO: A Comprehensive Database of Traditional Chinese Medicine on Immuno-Oncology},      
	
JOURNAL={Frontiers in Pharmacology},      
	
VOLUME={11},           
	
YEAR={2020},      
	  
URL={https://www.frontiersin.org/articles/10.3389/fphar.2020.00439},       
	
DOI={10.3389/fphar.2020.00439},      
	
ISSN={1663-9812},   
   
ABSTRACT={Advances in immuno-oncology (IO) are making immunotherapy a powerful tool for cancer treatment. With the discovery of an increasing number of IO targets, many herbs or ingredients from traditional Chinese medicine (TCM) have shown immunomodulatory function and antitumor effects via targeting the immune system. However, knowledge of underlying mechanisms is limited due to the complexity of TCM, which has multiple ingredients acting on multiple targets. To address this issue, we present TCMIO, a comprehensive database of Traditional Chinese Medicine on Immuno-Oncology, which can be used to explore the molecular mechanisms of TCM in modulating the cancer immune microenvironment. Over 120,000 small molecules against 400 IO targets were extracted from public databases and the literature. These ligands were further mapped to the chemical ingredients of TCM to identify herbs that interact with the IO targets. Furthermore, we applied a network inference-based approach to identify the potential IO targets of natural products in TCM. All of these data, along with cheminformatics and bioinformatics tools, were integrated into the publicly accessible database. Chemical structure mining tools are provided to explore the chemical ingredients and ligands against IO targets. Herb–ingredient–target networks can be generated online, and pathway enrichment analysis for TCM or prescription is available. This database is functional for chemical ingredient structure mining and network analysis for TCM. We believe that this database provides a comprehensive resource for further research on the exploration of the mechanisms of TCM in cancer immunity and TCM-inspired identification of novel drug leads for cancer immunotherapy. TCMIO can be publicly accessed at http://tcmio.xielab.net.}
}


@article{doi:10.1021/ci300604z,
author = {Koes, David Ryan and Baumgartner, Matthew P. and Camacho, Carlos J.},
title = {Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise},
journal = {Journal of Chemical Information and Modeling},
volume = {53},
number = {8},
pages = {1893-1904},
year = {2013},
doi = {10.1021/ci300604z},
    note ={PMID: 23379370},

URL = { 
        https://doi.org/10.1021/ci300604z
    
},
eprint = { 
        https://doi.org/10.1021/ci300604z
    
}

}

@article{https://doi.org/10.1002/wcms.1606,
author = {Neese, Frank},
title = {Software update: The ORCA program system—Version 5.0},
journal = {WIREs Computational Molecular Science},
volume = {12},
number = {5},
pages = {e1606},
keywords = {density functional theory, electron correlation, QM/MM, quantum chemistry, theoretical spectroscopy},
doi = {https://doi.org/10.1002/wcms.1606},
url = {https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/wcms.1606},
eprint = {https://wires.onlinelibrary.wiley.com/doi/pdf/10.1002/wcms.1606},
abstract = {Abstract Version 5.0 of the ORCA quantum chemistry program suite was released in July 2021. ORCA 5.0 represents a major improvement over all previous versions of ORCA and features (1) highly improved performance, (2) increased numerical robustness, (3) a host of new functionality, and (4) greatly improved user friendliness. The article describes the most salient features of the program. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Data Science > Computer Algorithms and Programming Software > Quantum Chemistry},
year = {2022}
}

@article{https://doi.org/10.1002/jcc.22885,
author = {Lu, Tian and Chen, Feiwu},
title = {Multiwfn: A multifunctional wavefunction analyzer},
journal = {Journal of Computational Chemistry},
volume = {33},
number = {5},
pages = {580-592},
keywords = {wavefunction analysis, orbital composition, population analysis, real space function, electron localization function},
doi = {https://doi.org/10.1002/jcc.22885},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.22885},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.22885},
abstract = {Abstract Multiwfn is a multifunctional program for wavefunction analysis. Its main functions are: (1) Calculating and visualizing real space function, such as electrostatic potential and electron localization function at point, in a line, in a plane or in a spatial scope. (2) Population analysis. (3) Bond order analysis. (4) Orbital composition analysis. (5) Plot density-of-states and spectrum. (6) Topology analysis for electron density. Some other useful utilities involved in quantum chemistry studies are also provided. The built-in graph module enables the results of wavefunction analysis to be plotted directly or exported to high-quality graphic file. The program interface is very user-friendly and suitable for both research and teaching purpose. The code of Multiwfn is substantially optimized and parallelized. Its efficiency is demonstrated to be significantly higher than related programs with the same functions. Five practical examples involving a wide variety of systems and analysis methods are given to illustrate the usefulness of Multiwfn. The program is free of charge and open-source. Its precompiled file and source codes are available from http://multiwfn.codeplex.com. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011},
year = {2012}
}

@Article{D1CP02805G,
author ="Zhang, Jun and Lu, Tian",
title  ="Efficient evaluation of electrostatic potential with computerized optimized code",
journal  ="Phys. Chem. Chem. Phys.",
year  ="2021",
volume  ="23",
issue  ="36",
pages  ="20323-20328",
publisher  ="The Royal Society of Chemistry",
doi  ="10.1039/D1CP02805G",
url  ="http://dx.doi.org/10.1039/D1CP02805G",
abstract  ="The evaluation of molecular electrostatic potential (ESP) is a performance bottleneck for many computational chemical tasks like restrained ESP charge fitting or quantum mechanics/molecular mechanics simulations. In this paper{,} an efficient algorithm for the evaluation of ESP is proposed. It regroups the expression in terms of primitive Gaussian type orbitals (GTOs) with identical angular momentum types and nuclei centers. Each term is calculated using a computerized optimized code. This algorithm was integrated into the wavefunction analysis program Multiwfn and was tested on several large systems. In the cases of dopamine and remdesivir{,} the performance of this algorithm was comparable to or better than some popular state-of-the-art codes. For meta1–organic framework-5{,} where the number of GTOs and ESP points is 4840 and 259 262{,} respectively{,} our code could finish the evaluation in 1874 seconds on ordinary hardware. It also exhibits good parallelization scaling. The source code of this algorithm is freely available and can become a useful tool for computational chemists."}


@software{pymol,
  author={Schrödinger, LLC and Warren DeLano},
  title={PyMOL},
  url={http://www.pymol.org/pymol},
  version = {2.4.0},
  date = {2020-05-20},
}